B‑precursor acute lymphoblastic leukemia (B‑ALL) is the most common cancer diagnosed in children and adolescents. Despite the fact that the 5‑year survival rate has increased from 60 to 90%, approximately a quarter of children suffer from relapse with poor outcome. To improve the clinical management of B‑ALL, there is an urgent need for prognostic biomarkers for the prediction of B‑ALL outcomes. In the present study, we performed a comprehensive analysis of the gene expression data of 456 samples from five independent cohorts. We first sought to identify B‑ALL‑associated genes by differential gene expression analysis by applying linear models. Then, the statistical modelling was applied to identify candidates related to relapse‑free survival. We identified a total of 1,273 B‑ALL‑associated genes that have functions relevant to chemokine signaling. From these genes, 59 genes were identified as prognostic biomarkers. Based on expression patterns of these genes, we successfully distinguished high‑ and low‑risk groups of B‑ALL patients (log-rank test, P‑value=0.025). We further investigated the 59‑gene expression levels in ALL chemotherapy‑treated cohorts and identified 4 genes as potential drug targets associated with drug sensitivity. Our results provided a novel biomarker panel. By leveraging the large scale of data and statistical modelling, we believe this 59‑gene biomarker could help to unveil the mechanisms underlying B‑ALL progression and become potential drug targets.